class_docstr: A module for POS tagging using CRFSuite https://pypi.python.org/pypi/python-crfsuite
  
  >>> from nltk.tag import CRFTagger
  >>> ct = CRFTagger()  # doctest: +SKIP
  
  >>> train_data = [[('University','Noun'), ('is','Verb'), ('a','Det'), ('good','Adj'), ('place','Noun')],
  ... [('dog','Noun'),('eat','Verb'),('meat','Noun')]]
  
  >>> ct.train(train_data,'model.crf.tagger')  # doctest: +SKIP
  >>> ct.tag_sents([['dog','is','good'], ['Cat','eat','meat']])  # doctest: +SKIP
  [[('dog', 'Noun'), ('is', 'Verb'), ('good', 'Adj')], [('Cat', 'Noun'), ('eat', 'Verb'), ('meat', 'Noun')]]
  
  >>> gold_sentences = [[('dog','Noun'),('is','Verb'),('good','Adj')] , [('Cat','Noun'),('eat','Verb'), ('meat','Noun')]]
  >>> ct.accuracy(gold_sentences)  # doctest: +SKIP
  1.0
  
  Setting learned model file
  >>> ct = CRFTagger()  # doctest: +SKIP
  >>> ct.set_model_file('model.crf.tagger')  # doctest: +SKIP
  >>> ct.accuracy(gold_sentences)  # doctest: +SKIP
  1.0
docstr: Tag a sentence using Python CRFSuite Tagger. NB before using this function, user should specify the mode_file either by
  
  - Train a new model using ``train`` function
  - Use the pre-trained model which is set via ``set_model_file`` function
  
  :params tokens: list of tokens needed to tag.
  :type tokens: list(str)
  :return: list of tagged tokens.
  :rtype: list(tuple(str,str))
docstr_tok: ["Tag","a","sentence","using","Python","CRFSuite","Tagger",".","NB","before","using","this","function",",","user","should","specify","the","mode_file","either","by","-","Train","a","new","model","using","``","train","``","function","-","Use","the","pre-trained","model","which","is","set","via","``","set_model_file","``","function",":","params","tokens",":","list","of","tokens","needed","to","tag",".",":","type","tokens",":","list","(","str",")",":","return",":","list","of","tagged","tokens",".",":","rtype",":","list","(","tuple","(","str",",","str",")",")"]
code: def tag(self, tokens):
      """
      Tag a sentence using Python CRFSuite Tagger. NB before using this function, user should specify the mode_file either by
  
      - Train a new model using ``train`` function
      - Use the pre-trained model which is set via ``set_model_file`` function
  
      :params tokens: list of tokens needed to tag.
      :type tokens: list(str)
      :return: list of tagged tokens.
      :rtype: list(tuple(str,str))
      """
  
      return self.tag_sents([tokens])[0]
  
file_path: nltk/nltk/tag/crf.py
imports: import re
  import unicodedata
  from nltk.tag.api import TaggerI
label_desc: Use image node_id 6 for calling the CRFTagger obj's underlying member method code with example usage: obj.tag(tokens) and returns: self